Assistant Researcher in Neurosurgery Machine Learning

University of California Los Angeles School of Medicine

United States

Assistant Researcher for Neurosurgery Machine Learning Laboratory

Job #JPF05558
  • David Geffen School Of Medicin - NEUROSURGERY

Recruitment Period

Open date: May 25th, 2020

Next review date: Wednesday, Jun 24, 2020 at 11:59pm (Pacific Time)

Apply by this date to ensure full consideration by the committee.

Final date: Wednesday, Jun 24, 2020 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.


The Department of Neurosurgery at the David Geffen School of Medicine at UCLA is seeking a qualified individual at the Assistant rank in the Professional Researcher Series to join the UCLA Department of Neurosurgery.

Candidates must have a Ph.D in Biomedical Engineering. Candidates should have experience in research areas that include but are not exclusive to basic and applied research at the intersection of spine image analysis, applied mathematics and machine learning. A consistent publication record demonstrating commitment to spine image analysis using machine learning is expected. This position requires a minimum of 5 years’ of postdoctoral experience in machine learning as applied to spine image analysis, with specific applications in the field of cervical and lumbar spinal MRI, X-Rays and CT.

Thorough knowledge of the continually evolving landscape of machine learning algorithms, the mathematics of the underlying non-convex optimization methodologies and an understanding of the challenges for operationalizing such algorithms in data sparse as well as data rich environments is necessary. An understanding of the DICOM protocol, radiology information systems and electronic health records is also expected, to perform the duties involved. Incumbents will be expected to design and lead studies, write scientific manuscripts, and assist or independently prepare and submit grant proposals for to advancing state-of-the-art in spine image analysis using machine learning. Clinical translation and education are key goals of this position as this position will involve supervising and teaching of trainees including undergraduate, graduate, medical students, post-doctoral fellows and residents.

The UCLA Department of Neurosurgery is particularly interested in candidates who have experience working with individuals from a diverse background and a demonstrated commitment to improving access to research opportunities for disadvantaged students. The Department is committed to building a more diverse faculty, staff and student body as it responds to the changing population and education needs of California and the nation.
Interested applicants must submit their application materials online at:

All inquiries related to this position and/or search may be directed to:

Luke Macyszyn, MD, MA
Assistant Professor, Department of Neurosurgery

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: UC Nondiscrimination and Affirmative Action Policy.

Job location

Los Angeles, CA


Document requirements
  • Curriculum Vitae - Your most recently updated C.V.
  • Cover Letter
  • Statement on Contributions to Equity, Diversity, and Inclusion - An EDI Statement describes a faculty candidate’s past, present, and future (planned) contributions to equity, diversity, and inclusion. To learn more about how UCLA thinks about contributions to equity, diversity, and inclusion, please review our Sample Guidance for Candidates and related EDI Statement FAQ document.
Reference requirements
  • 3-5 required (contact information only)

In your application, please refer to


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